Design Of Indoor Positioning System Based On RFID

Modern communication technology and information processing technology have been greatly developed in recent years.Under such a background,positioning technologies for indoor environments are gradually emerging.The application of RFID(Radio Frequency Identification,RFID)technology in indoor environments is becoming more and more widespread.According to the application of RFID technology in indoor positioning,this thesis develops an indoor positioning system using RFID technology,and designs the algorithm of the system.The indoor positioning system designed in this thesis aims at high positioning accuracy,short matching time,and low cost.After consulting a large number of references,this thesis analyzes and summarizes the current research status of indoor positioning technology at home and abroad,and studies several commonly used indoor positioning algorithms.Through the comparison of various methods,this thesis finally selected the location fingerprint-based positioning method as the research direction,and finally designed and implemented the proposed indoor positioning system.The traditional indoor fingerprint-based indoor positioning method has a large workload in collecting fingerprint points during the offline phase.Through the research and analysis of typical systems,this thesis uses interpolation algorithm to expand the fingerprint database.The indoor positioning system designed in this thesis uses Kriging interpolation algorithm to expand the offline fingerprint database,so as to reduce the workload of fingerprint points collection.Under traditional methods,the accuracy of indoor positioning methods based on location fingerprints depends on a large amount of fingerprint points in the offline fingerprint database.The larger the area of the positioning area,the more fingerprint points the system needs.The kriging interpolation algorithm takes the fingerprint points actually collected as reference points,and uses its spatial distribution characteristics to perform interpolation calculations to achieve the purpose of expanding the offline fingerprint database.The use of this method effectively reduces the workload of fingerprint points collection and has good performance in subsequent positioning work.In order to achieve the expected function,at first,this thesis analyzes the RSSI(Received Signal Strength Indication,RSSI)signal characteristics,including the introduction and fitting of its logarithmic path loss model.Then,the Gaussian filtering algorithm is used to pre-process the collected RSSI data to ensure the stability and representativeness of the data.Then,the application of Kriging interpolation algorithm in the system is realized,and the result of the interpolation calculation is compared with the RSSI data collected in the actual positioning area to analyze the error.Next,the UJIIndoor Loc database is used to assist the algorithm verification work,the K-means++ algorithm is used to cluster the fingerprint database,and the clustering effect is optimized by replacing the RSSI data vector with physical coordinates as the clustering basis.On the basis of the previous,WKNN algorithm is used to calculate the coordinates of the point to be located and the error of the positioning result is analyzed.The positioning accuracy performs well.Finally,the actual test environment and data processing platform are built.In terms of actual effect,the interpolation points in the established offline fingerprint database account for 37.7% of the total number of fingerprint points,which improves the efficiency of establishing the fingerprint database.The positioning results displayed in the user interaction interface prove that the functions of the design system in this thesis basically meet expectations.